肘板趾端表面裂纹在随机波浪载荷作用下的疲劳扩展预报

肘板趾端是船舶与海洋结构的疲劳热点。文章用三维有限元分析了趾端表面裂纹应力强度因子修正系数的变化规律,并与BS7910推荐的典型节点表面裂纹应力强度因子公式计算结果作了对比,结果表明趾端表面裂纹应力强度因子沿深度方向的放大系数和T型节点相差很小,而表面端点应力强度因子修正系数则当裂纹长度在肘板厚度范围内时和T型节点相差很小,超出后则相差较大。以某客滚船上肘板趾端应力范围长期分布服从Weibull分布,产生系列均值为零的应力幅,应力强度因子分别采用有限元结果和BS7910中T型接头公式进行计算,采用单一曲线模型计算该趾端表面裂纹的裂纹扩展。计算等效应力强度因子幅时,考虑焊接残余应力的影响。计算结果表明以T型接头的公式计算趾端表面裂纹应力强度因子和有限元结果相差很小。建议将T型节点表面裂纹应力强度因子计算公式用于趾端表面裂纹应力强度因子的计算,并采用单一曲线模型对随机波浪载荷下作用下船舶典型节点疲劳裂纹的扩展寿命进行了预报。     

基于粒子群算法的出口集装箱堆场箱位分配研究

码头堆场中出口集装箱的箱位分配是典型的NP-hard优化问题,考虑集装箱的质量及目的港,以出口集装箱的装船路径和堆区的翻箱率为目标,建立适合出口集装箱堆场箱位分配的数学模型,以粒子群算法进行求解,数据实验表明该模型能够提高堆场的作业效率,具有一定的的实用性.     

卫星通信地球站干扰条件下性能仿真与分析

文章分析了地球站在干扰情况下系统误码率计算方法,谈论了卫星通信中主要的干扰信号样式,并给出了几种常见干扰信号的表达式和功率谱密度,然后利用MATLAB/Simulink建立了卫星通信干扰模型,分别仿真了单音信号,多音信号和脉冲信号干扰地球站接收系统。通过仿真分析,得到了三种干扰信号对地球站的干扰效果,对地球站抗干扰具有指导意义。     

一种改进的疲劳裂纹扩展表达式

疲劳裂纹扩展率表达式是采用疲劳裂纹扩展理论预报疲劳寿命的核心.迄今为止,已有上百种不同的疲劳裂纹扩展率公式被提出.近年来,作者们致力于对新近提出的裂纹扩展率公式进行比较研究.通过初步研究发现,McEvily公式能解释比较多的异常疲劳现象,因此,它有比较强的预报能力,值得作深入研究.本文针对它采用固定斜率不能与很多实验结果有很好拟合的缺点,提出采用变斜率的改进形式.通过采用不同材料(钛合金D16Cz、铝合金D16Cz、ARMCO-iron)、不同应力条件(R≥0、R＜0、R=-∞)下的疲劳裂纹扩展数据进行分析验证,发现不管是疲劳短裂纹扩展还是疲劳长裂纹扩展,改进后的McEvily关系均具有良好的疲劳性能预测能力.     

接触网雷击跳闸率的新算法

结合接触网的受雷情况和结构特点建立接触网的雷击模型,分别给出线路遭受直接雷击和感应雷击时接触网的耐雷水平计算公式。基于广义积分法,提出计入感应雷击的计算接触网雷击跳闸率的方法。以常见的复线接触网为例,按照给出的模型和计算方法计算接触网的跳闸率,并将计算结果与实际情况比较。研究结果表明:接触网遭受感应雷击时的耐雷水平较低,因感应雷击造成的接触网雷击跳闸次数占总雷击跳闸次数的31.6%,感应雷击对接触网的跳闸影响是明显的;计入感应雷击计算的总跳闸次数更接近实际运行值。     

盾构泡沫剂的性能指标测试与分析

目前国内盾构泡沫剂产品尚未形成统一的评价标准,性能指标的选取与参数范围的界定也存在分歧。同时,针对产品的研究也大部分集中于末端应用方面,在基础性能的分析及其指标测试方面的研究工作较少。以市场上常见的6种泡沫剂为研究对象,通过其性能指标的测试与分析,给出合理的参数范围;并以此为依据,探究其中的相互关系与影响,特别增加了泡沫液与黏土接触角、泡沫膨胀损失率这两项性能指标,用于分析泡沫液与黏土表面的作用关系和盾构泡沫剂的发泡能力,说明其必要性,并给出合理的参考范围,其中泡沫液与黏土接触角通常在13°~30°之间,泡沫膨胀损失率应低于10。研究成果可为行业标准的出台提供技术支持。     

A nested recursive logit model for route choice analysis

We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link choices and the model does not require any sampling of choice sets. Furthermore, the model can be consistently estimated and efficiently used for prediction.A key challenge lies in the computation of the value functions, i.e. the expected maximum utility from any position in the network to a destination. The value functions are the solution to a system of non-linear equations. We propose an iterative method with dynamic accuracy that allows to efficiently solve these systems.We report estimation results and a cross-validation study for a real network. The results show that the NRL model yields sensible parameter estimates and the fit is significantly better than the RL model. Moreover, the NRL model outperforms the RL model in terms of prediction.     

滑差对贝氏体钢轨材料磨损行为的影响

通过对磨试验研究接触应力相同时贝氏体钢轨的磨损率、表面粗糙度、硬度,并结合扫描电镜观测到的磨损表面和剖面的形貌特征,分析不同滑差条件下贝氏体钢轨的磨损行为特征和变化规律.结果表明:接触应力为500 MPa条件下,贝氏体钢轨磨损率随滑差的增大而显著增大,滑差由2%增大到10%时磨损率增大了8倍;小滑差条件下的贝氏体钢轨表面较光滑,有少量疲劳裂纹,以滚动接触疲劳磨损为主;大滑差条件下表面粗糙,有疲劳裂纹、剥落坑和表面划擦痕迹,更接近滑动磨损;增大滑差可导致磨损表面加工硬化率偏大;增大滑差对贝氏体钢轨表面的滚动接触疲劳裂纹在深度方向的扩展几乎无影响,且对塑性变形层厚度影响不明显;大滑差可引发亚表面次表层裂纹.     

Factors affecting public transportation usage rate: Geographically weighted regression

As the number of private vehicles grows worldwide, so does air pollution and traffic congestion, which typically constrain economic development. To achieve transportation sustainability and continued economic development, the dependency on private vehicles must be decreased by increasing public transportation usage. However, without knowing the key factors that affect public transportation usage, developing strategies that effectively improve public transportation usage is impossible. Therefore, this study respectively applies global and local regression models to identify the key factors of usage rates for 348 regions (township or districts) in Taiwan. The global regression model, the Tobit regression model (TRM), is used to estimate one set of parameters that are associated with explanatory variables and explain regional differences in usage rates, while the local regression model, geographically weighted regression (GWR), estimates parameters differently depending on spatial correlations among neighbouring regions. By referencing related studies, 32 potential explanatory variables in four categories, social-economic, land use, public transportation, and private transportation, are chosen. Model performance is compared in terms of mean absolute percentage error (MAPE) and spatial autocorrelation coefficient (Moran’ I). Estimation results show that the GWR model has better prediction accuracy and better accommodation of spatial autocorrelation. Seven variables are significantly tested, and most have parameters that differ across regions in Taiwan. Based on these findings, strategies are proposed that improve public transportation usage.